{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-title"
    ]
   },
   "source": [
    "# Multiclass Support Vector Machine exercise\n",
    "\n",
    "*Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more details see the [assignments page](http://vision.stanford.edu/teaching/cs231n/assignments.html) on the course website.*\n",
    "\n",
    "In this exercise you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Run some setup code for this notebook.\n",
    "import random\n",
    "import numpy as np\n",
    "from cs231n.data_utils import load_CIFAR10\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# This is a bit of magic to make matplotlib figures appear inline in the\n",
    "# notebook rather than in a new window.\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# Some more magic so that the notebook will reload external python modules;\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "source": [
    "## CIFAR-10 Data Loading and Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clear previously loaded data.\n",
      "Training data shape:  (50000, 32, 32, 3)\n",
      "Training labels shape:  (50000,)\n",
      "Test data shape:  (10000, 32, 32, 3)\n",
      "Test labels shape:  (10000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the raw CIFAR-10 data.\n",
    "cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "\n",
    "# Cleaning up variables to prevent loading data multiple times (which may cause memory issue)\n",
    "try:\n",
    "    del X_train, y_train\n",
    "    del X_test, y_test\n",
    "    print('Clear previously loaded data.')\n",
    "except:\n",
    "    pass\n",
    "\n",
    "X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "\n",
    "# As a sanity check, we print out the size of the training and test data.\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Training labels shape: ', y_train.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 70 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize some examples from the dataset.\n",
    "# We show a few examples of training images from each class.\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "num_classes = len(classes)\n",
    "samples_per_class = 7\n",
    "for y, cls in enumerate(classes):\n",
    "    idxs = np.flatnonzero(y_train == y)\n",
    "    idxs = np.random.choice(idxs, samples_per_class, replace=False)\n",
    "    for i, idx in enumerate(idxs):\n",
    "        plt_idx = i * num_classes + y + 1\n",
    "        plt.subplot(samples_per_class, num_classes, plt_idx)\n",
    "        plt.imshow(X_train[idx].astype('uint8'))\n",
    "        plt.axis('off')\n",
    "        if i == 0:\n",
    "            plt.title(cls)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 32, 32, 3)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 32, 32, 3)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 32, 32, 3)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Split the data into train, val, and test sets. In addition we will\n",
    "# create a small development set as a subset of the training data;\n",
    "# we can use this for development so our code runs faster.\n",
    "num_training = 49000\n",
    "num_validation = 1000\n",
    "num_test = 1000\n",
    "num_dev = 500\n",
    "\n",
    "# Our validation set will be num_validation points from the original\n",
    "# training set.\n",
    "mask = range(num_training, num_training + num_validation)\n",
    "X_val = X_train[mask]\n",
    "y_val = y_train[mask]\n",
    "\n",
    "# Our training set will be the first num_train points from the original\n",
    "# training set.\n",
    "mask = range(num_training)\n",
    "X_train = X_train[mask]\n",
    "y_train = y_train[mask]\n",
    "\n",
    "# We will also make a development set, which is a small subset of\n",
    "# the training set.\n",
    "mask = np.random.choice(num_training, num_dev, replace=False)\n",
    "X_dev = X_train[mask]\n",
    "y_dev = y_train[mask]\n",
    "\n",
    "# We use the first num_test points of the original test set as our\n",
    "# test set.\n",
    "mask = range(num_test)\n",
    "X_test = X_test[mask]\n",
    "y_test = y_test[mask]\n",
    "\n",
    "print('Train data shape: ', X_train.shape)\n",
    "print('Train labels shape: ', y_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Validation labels shape: ', y_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training data shape:  (49000, 3072)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Test data shape:  (1000, 3072)\n",
      "dev data shape:  (500, 3072)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: reshape the image data into rows\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], -1))\n",
    "X_val = np.reshape(X_val, (X_val.shape[0], -1))\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], -1))\n",
    "X_dev = np.reshape(X_dev, (X_dev.shape[0], -1))\n",
    "\n",
    "# As a sanity check, print out the shapes of the data\n",
    "print('Training data shape: ', X_train.shape)\n",
    "print('Validation data shape: ', X_val.shape)\n",
    "print('Test data shape: ', X_test.shape)\n",
    "print('dev data shape: ', X_dev.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[130.64189796 135.98173469 132.47391837 130.05569388 135.34804082\n",
      " 131.75402041 130.96055102 136.14328571 132.47636735 131.48467347]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49000, 3073) (1000, 3073) (1000, 3073) (500, 3073)\n"
     ]
    }
   ],
   "source": [
    "# Preprocessing: subtract the mean image\n",
    "# first: compute the image mean based on the training data, pixel-wise\n",
    "mean_image = np.mean(X_train, axis=0)\n",
    "print(mean_image[:10]) # print a few of the elements\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.imshow(mean_image.reshape((32,32,3)).astype('uint8')) # visualize the mean image\n",
    "plt.show()\n",
    "\n",
    "# second: subtract the mean image from train and test data\n",
    "X_train -= mean_image\n",
    "X_val -= mean_image\n",
    "X_test -= mean_image\n",
    "X_dev -= mean_image\n",
    "\n",
    "# third: append the bias dimension of ones (i.e. bias trick) so that our SVM\n",
    "# only has to worry about optimizing a single weight matrix W.\n",
    "X_train = np.hstack([X_train, np.ones((X_train.shape[0], 1))])\n",
    "X_val = np.hstack([X_val, np.ones((X_val.shape[0], 1))])\n",
    "X_test = np.hstack([X_test, np.ones((X_test.shape[0], 1))])\n",
    "X_dev = np.hstack([X_dev, np.ones((X_dev.shape[0], 1))])\n",
    "\n",
    "print(X_train.shape, X_val.shape, X_test.shape, X_dev.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SVM Classifier\n",
    "\n",
    "Your code for this section will all be written inside **cs231n/classifiers/linear_svm.py**. \n",
    "\n",
    "As you can see, we have prefilled the function `compute_loss_naive` which uses for loops to evaluate the multiclass SVM loss function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 8.545272\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the naive implementation of the loss we provided for you:\n",
    "from cs231n.classifiers.linear_svm import svm_loss_naive\n",
    "import time\n",
    "\n",
    "# generate a random SVM weight matrix of small numbers\n",
    "W = np.random.randn(3073, 10) * 0.0001 \n",
    "\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `grad` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have correctly implemented the gradient correctly, you can numerically estimate the gradient of the loss function and compare the numeric estimate to the gradient that you computed. We have provided code that does this for you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 17.552235 analytic: 17.552235, relative error: 1.751184e-11\n",
      "numerical: 14.743516 analytic: 14.708440, relative error: 1.190960e-03\n",
      "numerical: -25.214613 analytic: -25.214613, relative error: 2.542945e-12\n",
      "numerical: 0.398110 analytic: 0.398110, relative error: 9.733423e-10\n",
      "numerical: 6.168824 analytic: 6.168824, relative error: 1.337323e-11\n",
      "numerical: 8.211196 analytic: 8.211196, relative error: 2.059776e-11\n",
      "numerical: 25.631525 analytic: 25.631525, relative error: 3.566987e-12\n",
      "numerical: 14.260246 analytic: 14.260246, relative error: 9.273706e-12\n",
      "numerical: -22.298877 analytic: -22.282418, relative error: 3.691839e-04\n",
      "numerical: -6.489246 analytic: -6.489246, relative error: 7.310736e-12\n",
      "numerical: -20.107835 analytic: -20.092980, relative error: 3.695058e-04\n",
      "numerical: 7.801251 analytic: 7.801251, relative error: 5.106890e-11\n",
      "numerical: 21.723702 analytic: 21.723702, relative error: 1.097261e-11\n",
      "numerical: 2.644731 analytic: 2.644731, relative error: 1.642174e-10\n",
      "numerical: -4.881881 analytic: -4.881881, relative error: 3.310010e-11\n",
      "numerical: 5.184514 analytic: 5.184514, relative error: 8.935784e-11\n",
      "numerical: -34.051518 analytic: -34.121385, relative error: 1.024845e-03\n",
      "numerical: -5.679509 analytic: -5.679509, relative error: 2.587333e-11\n",
      "numerical: 13.232753 analytic: 13.232753, relative error: 2.461212e-12\n",
      "numerical: 9.262877 analytic: 9.262877, relative error: 1.867146e-11\n"
     ]
    }
   ],
   "source": [
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should match\n",
    "# almost exactly along all dimensions.\n",
    "from cs231n.gradient_check import grad_check_sparse\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 0.0)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)\n",
    "\n",
    "# do the gradient check once again with regularization turned on\n",
    "# you didn't forget the regularization gradient did you?\n",
    "loss, grad = svm_loss_naive(W, X_dev, y_dev, 5e1)\n",
    "f = lambda w: svm_loss_naive(w, X_dev, y_dev, 5e1)[0]\n",
    "grad_numerical = grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline Question 1**\n",
    "\n",
    "It is possible that once in a while a dimension in the gradcheck will not match exactly. What could such a discrepancy be caused by? Is it a reason for concern? What is a simple example in one dimension where a gradient check could fail? How would change the margin affect of the frequency of this happening? *Hint: the SVM loss function is not strictly speaking differentiable*\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ *If the gradient is calculated near the turning point of hinge loss, where the derivative is not well-defined, there will be discrepancies between analytic results and numerical results. Analytic results are always accurate, while numerical errors could make numerical gradients not accurate.*  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 8.545272e+00 computed in 0.396057s\n",
      "Vectorized loss: 8.545272e+00 computed in 0.051276s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Next implement the function svm_loss_vectorized; for now only compute the loss;\n",
    "# we will implement the gradient in a moment.\n",
    "tic = time.time()\n",
    "loss_naive, _ = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss: %e computed in %fs' % (loss_naive, toc - tic))\n",
    "\n",
    "from cs231n.classifiers.linear_svm import svm_loss_vectorized\n",
    "tic = time.time()\n",
    "loss_vectorized, _ = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss: %e computed in %fs' % (loss_vectorized, toc - tic))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('difference: %f' % (loss_naive - loss_vectorized))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss and gradient: computed in 0.358653s\n",
      "Vectorized loss and gradient: computed in 0.002439s\n",
      "difference: 0.000000\n"
     ]
    }
   ],
   "source": [
    "# Complete the implementation of svm_loss_vectorized, and compute the gradient\n",
    "# of the loss function in a vectorized way.\n",
    "\n",
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Naive loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "tic = time.time()\n",
    "_, grad_vectorized = svm_loss_vectorized(W, X_dev, y_dev, 0.000005)\n",
    "toc = time.time()\n",
    "print('Vectorized loss and gradient: computed in %fs' % (toc - tic))\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a matrix, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "difference = np.linalg.norm(grad_naive - grad_vectorized, ord='fro')\n",
    "print('difference: %f' % difference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stochastic Gradient Descent\n",
    "\n",
    "We now have vectorized and efficient expressions for the loss, the gradient and our gradient matches the numerical gradient. We are therefore ready to do SGD to minimize the loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 791.422481\n",
      "iteration 100 / 1500: loss 289.455623\n",
      "iteration 200 / 1500: loss 108.638344\n",
      "iteration 300 / 1500: loss 42.849159\n",
      "iteration 400 / 1500: loss 19.141447\n",
      "iteration 500 / 1500: loss 10.337726\n",
      "iteration 600 / 1500: loss 6.833885\n",
      "iteration 700 / 1500: loss 5.500406\n",
      "iteration 800 / 1500: loss 6.291607\n",
      "iteration 900 / 1500: loss 5.492753\n",
      "iteration 1000 / 1500: loss 4.931398\n",
      "iteration 1100 / 1500: loss 5.210728\n",
      "iteration 1200 / 1500: loss 5.009100\n",
      "iteration 1300 / 1500: loss 5.155179\n",
      "iteration 1400 / 1500: loss 5.670465\n",
      "That took 3.719821s\n"
     ]
    }
   ],
   "source": [
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "tic = time.time()\n",
    "loss_hist = svm.train(X_train, y_train, learning_rate=1e-7, reg=2.5e4,\n",
    "                      num_iters=1500, verbose=True)\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A useful debugging strategy is to plot the loss as a function of\n",
    "# iteration number:\n",
    "plt.plot(loss_hist)\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 0.372531\n",
      "validation accuracy: 0.381000\n"
     ]
    }
   ],
   "source": [
    "# Write the LinearSVM.predict function and evaluate the performance on both the\n",
    "# training and validation set\n",
    "y_train_pred = svm.predict(X_train)\n",
    "print('training accuracy: %f' % (np.mean(y_train == y_train_pred), ))\n",
    "y_val_pred = svm.predict(X_val)\n",
    "print('validation accuracy: %f' % (np.mean(y_val == y_val_pred), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {
    "tags": [
     "code"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr 1.000000e-08 reg 1.000000e+04 train accuracy: 0.243061 val accuracy: 0.246000\n",
      "lr 1.000000e-08 reg 2.000000e+04 train accuracy: 0.289367 val accuracy: 0.312000\n",
      "lr 1.000000e-08 reg 3.000000e+04 train accuracy: 0.349714 val accuracy: 0.355000\n",
      "lr 1.000000e-08 reg 4.000000e+04 train accuracy: 0.368694 val accuracy: 0.366000\n",
      "lr 1.000000e-08 reg 5.000000e+04 train accuracy: 0.365857 val accuracy: 0.374000\n",
      "lr 1.000000e-08 reg 6.000000e+04 train accuracy: 0.362531 val accuracy: 0.382000\n",
      "lr 1.000000e-08 reg 7.000000e+04 train accuracy: 0.356714 val accuracy: 0.376000\n",
      "lr 1.000000e-08 reg 8.000000e+04 train accuracy: 0.354061 val accuracy: 0.363000\n",
      "lr 1.000000e-08 reg 9.000000e+04 train accuracy: 0.349449 val accuracy: 0.357000\n",
      "lr 5.000000e-08 reg 1.000000e+04 train accuracy: 0.382327 val accuracy: 0.392000\n",
      "lr 5.000000e-08 reg 2.000000e+04 train accuracy: 0.374735 val accuracy: 0.378000\n",
      "lr 5.000000e-08 reg 3.000000e+04 train accuracy: 0.370367 val accuracy: 0.376000\n",
      "lr 5.000000e-08 reg 4.000000e+04 train accuracy: 0.365714 val accuracy: 0.380000\n",
      "lr 5.000000e-08 reg 5.000000e+04 train accuracy: 0.360571 val accuracy: 0.372000\n",
      "lr 5.000000e-08 reg 6.000000e+04 train accuracy: 0.359204 val accuracy: 0.366000\n",
      "lr 5.000000e-08 reg 7.000000e+04 train accuracy: 0.351388 val accuracy: 0.356000\n",
      "lr 5.000000e-08 reg 8.000000e+04 train accuracy: 0.348082 val accuracy: 0.372000\n",
      "lr 5.000000e-08 reg 9.000000e+04 train accuracy: 0.347531 val accuracy: 0.365000\n",
      "lr 1.000000e-07 reg 1.000000e+04 train accuracy: 0.390776 val accuracy: 0.394000\n",
      "lr 1.000000e-07 reg 2.000000e+04 train accuracy: 0.373184 val accuracy: 0.379000\n",
      "lr 1.000000e-07 reg 3.000000e+04 train accuracy: 0.365918 val accuracy: 0.376000\n",
      "lr 1.000000e-07 reg 4.000000e+04 train accuracy: 0.357959 val accuracy: 0.364000\n",
      "lr 1.000000e-07 reg 5.000000e+04 train accuracy: 0.356469 val accuracy: 0.361000\n",
      "lr 1.000000e-07 reg 6.000000e+04 train accuracy: 0.352367 val accuracy: 0.361000\n",
      "lr 1.000000e-07 reg 7.000000e+04 train accuracy: 0.350265 val accuracy: 0.364000\n",
      "lr 1.000000e-07 reg 8.000000e+04 train accuracy: 0.349306 val accuracy: 0.365000\n",
      "lr 1.000000e-07 reg 9.000000e+04 train accuracy: 0.347163 val accuracy: 0.355000\n",
      "lr 5.000000e-07 reg 1.000000e+04 train accuracy: 0.342735 val accuracy: 0.353000\n",
      "lr 5.000000e-07 reg 2.000000e+04 train accuracy: 0.303469 val accuracy: 0.330000\n",
      "lr 5.000000e-07 reg 3.000000e+04 train accuracy: 0.310224 val accuracy: 0.325000\n",
      "lr 5.000000e-07 reg 4.000000e+04 train accuracy: 0.340918 val accuracy: 0.347000\n",
      "lr 5.000000e-07 reg 5.000000e+04 train accuracy: 0.292143 val accuracy: 0.302000\n",
      "lr 5.000000e-07 reg 6.000000e+04 train accuracy: 0.309184 val accuracy: 0.339000\n",
      "lr 5.000000e-07 reg 7.000000e+04 train accuracy: 0.317122 val accuracy: 0.343000\n",
      "lr 5.000000e-07 reg 8.000000e+04 train accuracy: 0.309898 val accuracy: 0.322000\n",
      "lr 5.000000e-07 reg 9.000000e+04 train accuracy: 0.320776 val accuracy: 0.340000\n",
      "lr 1.000000e-06 reg 1.000000e+04 train accuracy: 0.332143 val accuracy: 0.348000\n",
      "lr 1.000000e-06 reg 2.000000e+04 train accuracy: 0.286204 val accuracy: 0.300000\n",
      "lr 1.000000e-06 reg 3.000000e+04 train accuracy: 0.279388 val accuracy: 0.295000\n",
      "lr 1.000000e-06 reg 4.000000e+04 train accuracy: 0.242061 val accuracy: 0.254000\n",
      "lr 1.000000e-06 reg 5.000000e+04 train accuracy: 0.249408 val accuracy: 0.244000\n",
      "lr 1.000000e-06 reg 6.000000e+04 train accuracy: 0.306653 val accuracy: 0.308000\n",
      "lr 1.000000e-06 reg 7.000000e+04 train accuracy: 0.246347 val accuracy: 0.246000\n",
      "lr 1.000000e-06 reg 8.000000e+04 train accuracy: 0.260816 val accuracy: 0.272000\n",
      "lr 1.000000e-06 reg 9.000000e+04 train accuracy: 0.270857 val accuracy: 0.283000\n",
      "best validation accuracy achieved during cross-validation: 0.394000\n"
     ]
    }
   ],
   "source": [
    "# Use the validation set to tune hyperparameters (regularization strength and\n",
    "# learning rate). You should experiment with different ranges for the learning\n",
    "# rates and regularization strengths; if you are careful you should be able to\n",
    "# get a classification accuracy of about 0.39 on the validation set.\n",
    "\n",
    "#Note: you may see runtime/overflow warnings during hyper-parameter search. \n",
    "# This may be caused by extreme values, and is not a bug.\n",
    "\n",
    "learning_rates = [1e-8, 5e-8, 1e-7, 5e-7, 1e-6]\n",
    "regularization_strengths = np.arange(1, 10, 1) * 1e4 #[2.5e4, 5e4]\n",
    "\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (training_accuracy, validation_accuracy). The accuracy is simply the fraction\n",
    "# of data points that are correctly classified.\n",
    "results = {}\n",
    "best_val = -1   # The highest validation accuracy that we have seen so far.\n",
    "best_svm = None # The LinearSVM object that achieved the highest validation rate.\n",
    "\n",
    "################################################################################\n",
    "# TODO:                                                                        #\n",
    "# Write code that chooses the best hyperparameters by tuning on the validation #\n",
    "# set. For each combination of hyperparameters, train a linear SVM on the      #\n",
    "# training set, compute its accuracy on the training and validation sets, and  #\n",
    "# store these numbers in the results dictionary. In addition, store the best   #\n",
    "# validation accuracy in best_val and the LinearSVM object that achieves this  #\n",
    "# accuracy in best_svm.                                                        #\n",
    "#                                                                              #\n",
    "# Hint: You should use a small value for num_iters as you develop your         #\n",
    "# validation code so that the SVMs don't take much time to train; once you are #\n",
    "# confident that your validation code works, you should rerun the validation   #\n",
    "# code with a larger value for num_iters.                                      #\n",
    "################################################################################\n",
    "# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "# In the file linear_classifier.py, implement SGD in the function\n",
    "# LinearClassifier.train() and then run it with the code below.\n",
    "from cs231n.classifiers import LinearSVM\n",
    "svm = LinearSVM()\n",
    "for lr in learning_rates:\n",
    "    for reg in regularization_strengths:\n",
    "        _ = svm.train(X_train, y_train, learning_rate=lr, reg=reg,\n",
    "                      num_iters=1500, verbose=False)\n",
    "        y_train_pred = svm.predict(X_train)\n",
    "        y_val_pred = svm.predict(X_val)\n",
    "        val_accuracy = np.mean(y_val == y_val_pred)\n",
    "        train_accuracy = np.mean(y_train == y_train_pred)\n",
    "        results[(lr, reg)] = (train_accuracy, val_accuracy)\n",
    "        if val_accuracy > best_val:\n",
    "            best_val = val_accuracy\n",
    "            best_svm = svm\n",
    "            \n",
    "# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "    \n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr, reg)]\n",
    "    print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "                lr, reg, train_accuracy, val_accuracy))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the cross-validation results\n",
    "import math\n",
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap=plt.cm.coolwarm)\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.273000\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the best svm on test set\n",
    "y_test_pred = best_svm.predict(X_test)\n",
    "test_accuracy = np.mean(y_test == y_test_pred)\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {
    "tags": [
     "pdf-ignore-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the learned weights for each class.\n",
    "# Depending on your choice of learning rate and regularization strength, these may\n",
    "# or may not be nice to look at.\n",
    "w = best_svm.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(32, 32, 3, 10)\n",
    "w_min, w_max = np.min(w), np.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "    # Rescale the weights to be between 0 and 255\n",
    "    wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "    plt.imshow(wimg.astype('uint8'))\n",
    "    plt.axis('off')\n",
    "    plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "**Inline question 2**\n",
    "\n",
    "Describe what your visualized SVM weights look like, and offer a brief explanation for why they look they way that they do.\n",
    "\n",
    "$\\color{blue}{\\textit Your Answer:}$ *Bravo!!! Looks quite interesting!*  \n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
